Geology topics

Brian Daniel Gerber

Publications and source records attributed to Brian Daniel Gerber.

7 recordsLinked to original sources

USGS2026

White light reduces flight height of birds in low-density migration corridor

Artificial light at night (ALAN) has been shown to influence the behavior of migratory birds, yet how different light spectra modulate these effects remains unclear. We conducted a field experiment for 31 nights at a remote site in northern Colorado, USA, using 2 800-W light-emitting diode (LED) floodlights with white, red, amber, and blue lighting treatments during fall migration in 2023 and 2024. Using a vertical-looking radar system, we quantified avian in-flight responses in migration traffic rate, flight height, and flight direction between paired control periods with no light and periods with lighting treatments. Although we found no effects of our treatments on migration traffic rate and weak effects on flight direction, we found that broad-spectrum white light with emissions across a 400–600 nm spectrum reduced mean avian flight height by an estimated 22.57 m (±10.53 SE) compared to dark periods, and this response was stronger than red and blue lighting treatments. Our ability to detect behavior changes from a point source in a rural, low-density migration system supports the notion that the effects of artificial light at night on bird behavior may be more pervasive than is often recognized, and that this varies by ALAN spectra. Beyond providing insight into avian orientation and in-flight behavior, our results have implications for future research, the conservation management of artificial light at night, and lighting designs that minimize effects on migratory birds.

Colorado↗

USGS2026

Monitoring wolverine (Gulo gulo) distribution across the western United States for regional and national assessment

Population monitoring of at-risk species is fundamental to directing effective and timely conservation actions. For wide-ranging threatened species, such as the wolverine ( Gulo gulo ), monitoring across multiple jurisdictions is necessary to track their distribution to inform collaborative regional and national management and policy. We repeated a landscape-scale, multi-jurisdictional remote camera survey first completed in 2017 to evaluate wolverine occupancy throughout the western United States in 2022. Our objectives were to 1) expand the sampling frame to include areas of potential recolonization (Colorado, Oregon, Utah, USA), 2) evaluate whether overall and state-specific occurrence has changed from 2017 in the common sampling frame of Idaho, Montana, Washington, and Wyoming, USA, and 3) evaluate spatial drivers of wolverine occurrence in 2022. From a sampling frame of 770 sites (15 × 15-km cells) identified as potential wolverine habitat, 229 sites were surveyed in 2022; no wolverines were detected in Colorado, Oregon, or Utah. We predicted wolverine occupancy and 95% highest posterior density intervals (HPDI) in states with detections to be 0.47 (0.37–0.58) in Idaho, 0.35 (0.21–0.52) in Montana, 0.29 (0.09–0.54) in Washington, and 0.35 (0.27–0.47) in Wyoming. We found weak to moderate evidence of a small decline in overall occupancy ( 𝜓 ) from the common sampling frame (2017: 0.44 [0.37–0.52]; 2022: 0.39 [0.30–0.49]; P( 𝜓 2022 <𝜓 2017 ) = 0.81), driven by lower occurrences in Montana and Washington. However, this finding is complicated by a change in detection methodology that may have contributed to lower occurrences in Montana and Washington. Lastly, we found strong support (probability of an effect >0.95) that within areas of predicted wolverine habitat, increasing habitat connectivity and the proportion of a site that was previously burned (2001–2015) were associated with increased wolverine occupancy, while increasing normalized difference vegetation index (NDVI) was associated with decreased wolverine occupancy. Our expanded sampling frame provides the means to track wolverine occupancy and range extent—including recolonizations and contractions—across the western United States, providing insights at both the state and national scales.

Colorado, Idaho, Montana, Oregon, Utah, Washington↗

USGS2026

Microclimate mediates the strength and direction of avian biotic interactions

Theory predicts that that the strength and direction of species interactions can shift from being competitive in benign environments toward being facilitative in stressful environments. However, the environmental context dependency of species interactions has rarely been tested in animal communities. We capitalized on a 15-year, landscape-scale dataset, collected annually in a relatively stable old-growth forest environment to test the long-held hypothesis that the strength and direction of species interactions might be mediated by climatic conditions. It is generally accepted that competitive and facilitative interactions drive the distributions of many species. Using multi-species dynamic occupancy models applied to long-term data, we tested whether annual settlement by bird species could affect either the persistence or settlement by other phylogenetically related species, and whether these interactions are mediated by microclimate. We found that species interactions were influenced by microclimate for some, but not all avian species pairs. Related species pairs more often showed settlement dynamics that were indicative of attraction rather than repulsion. In some cases, competitive interactions at warmer microclimates flipped to become facilitative in colder ones. However, the reverse was also true: facilitative interactions amplified for some species under warm conditions. Furthermore, species pairs that were closely related were more likely to exhibit competitive relationships along at least part of the microclimatic gradient. Our results highlight the importance of using long-term data to incorporate competitive and facilitative interactions into species distribution models and support the notion that the strength and direction of species interactions can be dependent on microclimatic environmental conditions.

Oregon↗

USGS2026

Experimentally quantifying how long recreation noise displaces mammals: Recovery over weeks to months varies by disturbance type and species tolerance

Outdoor recreation is expanding across public lands, yet managers lack evidence for how long wildlife responses to recreation persist and whether response duration depends on disturbance type and frequency. Using a field-based acoustic playback experiment in the Bridger–Teton National Forest, Wyoming, USA, we isolated recreation noise from other components of human presence and quantified how long mammal detections took to return to baseline. Across 12 sites over two field seasons, we broadcast motorized and non-motorized recreation sounds at rates mimicking high- and low-use trails, paired with nature-sound controls. We quantified treatment effects as deviations from expected weekly detections at our control sites, defining time-to-return as the first week when deviations overlapped zero. Response duration differed between disturbance types. High-rate motorized playbacks produced the longest suppression: all species except mule deer did not return to baseline within our 15-week season, whereas mule deer recovered by six weeks. For high-rate non-motorized playbacks, all species except for mule deer had suppressed detections until seven weeks while mule deer detections were not different from baseline. For low-rate non-motorized playbacks, mule deer detections returned to baseline at nine weeks while all other species returned to baseline at seven weeks. Species differences indicate that apparent overall recovery can mask prolonged avoidance by less tolerant taxa. Recreation effects persisted for weeks to months and varied with disturbance type and exposure frequency, highlighting how temporal patterns of use influence wildlife responses and where recreational planning of spatial refugia or seasonal restrictions could reduce impacts on sensitive species.

Wyoming↗

USGS2025

Aggregating three sources of long-term trends of swallows and martins to identify priority conservation areas in the Great Lakes region

1. Long-term monitoring of bird populations across scales is important in evaluating conservation targets and creating effective conservation strategies. For nearly six decades, the Breeding Bird Survey (BBS) has served as the primary broad-scaled source of relative abundance trends of swallows and martins in North America. Recently, however, it has become possible to obtain breeding population trends using semi-structured eBird community science data. Moreover, weather surveil-lance radar data of swallow and martin roosting populations yield a third complementary source of trend information. 2. Using results from these three approaches, we propose a novel method of spatially combining estimates of percent change per year into a probability of directional agreement and/or disagreement that describes (1) the direction of the trend within a given region, (2) the amount of evidence associated with the estimate and (3) how much uncertainty surrounds it. We focus our efforts on an area of high Hirundinidae concentration in the North American Great Lakes region and predict trends from 2012 to 2022. 3. We found a high probability of agreement between all three sources about ob-served declines in swallow and martin trends in the region surrounding Lake Ontario and to the west of Lake Michigan. Focusing future research on these regions could improve our understanding of these declines and help build more targeted conservation initiatives. 4. Synthesis and applications. Our data integration methodology allows managers to identify regions that accumulate evidence of concerning trends across multiple wildlife monitoring schemes. These regions can thus be prioritized in conservation and management efforts. This approach can be generalized to other sources of long-term monitoring data of different species, at different stages of their annual cycle, in any geographic location.

Great Lakes region↗

USGS2025

Integrated species distribution model using historical data shows decline in a common semi-aquatic mammal

Effective conservation requires an understanding of drivers of a species' distribution as well as long-term changes in their distribution. In recent decades, advances in data collection and analysis have allowed researchers to integrate a wide range of information to model species distributions, particularly by allowing presence-only data and detection-nondetection data to be formally combined in integrated species distribution models (ISDMs). However, these models are rarely used to investigate long-term trends, which are important in evaluating a species' status. Here, we use historical presence-only data of river otters ( Lontra canadensis ; 366 latrine locations from 1999 to 2007 and 105 locations of road-killed individuals recorded from 1999 to 2020) and 919 detection-nondetection surveys from 230 sites between 2021 and 2023 to understand the current distribution of river otters in Rhode Island, USA, as well as the changes in river otter distribution over the past two decades. We found that river otters were strongly associated with key habitat features such as streams and water, positively associated with urban areas, and tolerant of some contaminants, such as lead. Furthermore, despite uncertainties in historical river otter occurrence, we found clear supporting evidence that river otter intensity of use had declined from 1999 to 2023. This decline occurred despite being protected from harvest and in contrast to range expansions in other parts of the northeastern USA throughout the second half of the 20th century. Our results suggest the utility of this approach to detect declines in species for which historical data are available and a need for better understanding the cause of river otter declines. Where monitoring consists of opportunistically collected data, species conservation could benefit by continuing to collect these data as well as introducing designed surveys, as this would allow better integration of data types, improving trend estimation and reducing the amount of (typically more expensive) designed surveys needed.

Rhode Island↗

USGS2024

A ‘how-to’ guide for estimating animal diel activity using hierarchical models

Animal diel activity patterns can aid understanding of (a) how species behaviourally adapt to anthropogenic and natural disturbances, (b) mechanisms of species co-existence through temporal partitioning, and (c) community or ecosystem effects of diel activity shifts. Activity patterns often vary spatially, a feature ignored by the kernel density estimators (KDEs) currently used for estimating diel activity. Ignoring this source of heterogeneity may lead to biased estimates of uncertainty and misleading conclusions regarding the drivers of diel activity. Thus, there is a need for more flexible statistical approaches for estimating activity patterns and testing hypotheses regarding their biotic and abiotic drivers. We illustrate how trigonometric terms and cyclic cubic splines combined with hierarchical models can provide a valuable alternative to KDEs. Like KDEs, these models accommodate circular data, but they can also account for site-to-site and other sources of variability, correlation amongst repeated measures, and variable sampling effort. They can also more readily quantify and test hypotheses related to the effects of covariates on activity patterns. Through empirical case studies, we illustrate how hierarchical models can quantify changes in activity levels due to seasonality and in response to biotic and abiotic factors (e.g. anthropogenic stressors and co-occurrence). We also describe frequentist and Bayesian approaches for quantifying site-specific (conditional) and population-averaged (marginal) activity patterns. We provide guidelines and tutorials with detailed step-by-step instructions for fitting and interpreting hierarchical models applied to time-stamped data, such as those recorded by camera traps and audio recorders. We conclude that this approach offers a viable, flexible, and effective alternative to KDEs when modelling animal activity patterns.

Journal of Animal Ecology↗